On Stability and Tuning of Neural Oscillators: Application to Rhythmic Control of a Humanoid Robot

Abstract

Neural oscillators offer a natural tool for exploiting and adapting to the dynamics of the controlled system. The capability of entraining the frequency of the input signal or resonance modes of dynamical systems have been increasingly used in robotics' mechanisms to accomplish complex tasks. However, the application of Matsuoka neural oscillators as controllers requires knowledge of the range of values for the parameters for which the system oscillates, and the warranty of stability. Thus, this paper studies in-depth the stability and tuning of Matsuoka neural oscillators, and presents a careful analysis of its behavior on the time-domain. The method is applied on a humanoid robot for playing musical instruments.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2004
Accession Number
ADA434751

Entities

People

  • Artur M. Arsenio

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Amplitude
  • Artificial Intelligence
  • Closed Loop Systems
  • Computer Science
  • Contracts
  • Dynamics
  • Eigenvalues
  • Eigenvectors
  • Equations
  • Frequency
  • Frequency Domain
  • Linear Systems
  • Oscillation
  • Oscillators
  • Quadrants
  • Time Domain
  • Vibration

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Optical Physics and Photonics.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Neural Networks
  • Autonomy
  • Autonomy - Autonomous System Control